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An Agent-Based Model of Discourse Pattern Formation in Small Groups of Competing and Cooperating Members

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  • Ismo T. Koponen
  • Maija Nousiainen

Abstract

Discourse patterns in a small group are assumed to form largely through the group's internal social dynamics when group members compete for floor in discourse. Here we approach such discourse pattern formation through the agent-based model (ABM). In the ABM introduced here the agents' interactions and participation in discussions are dependent on the agents' inherent potential activity to participate in discussion and on realised, externalised activity, discursivity. The discourse patterns are assumed to be outcomes of peer-to-peer comparison events, where agents competitively compare their activities and discursivities, and where activities also affect agents' cooperation in increasing the discursivity, i.e. floor for discourse. These two effects and their influence on discourse pattern formation are parameterised as comptetivity and cooperativity. The discourse patterns are here based on the agents' discursivity. The patterns in groups of four agents up to seven agents are characterised through triadic census (i.e. though counting triadic sub-patterns). The cases of low competitivity is shown to give rise to fully connected egalitarian, triadic patterns, which with increasing competitivity are transformed to strong dyadic patterns. An increase in cooperativity enhances the emergence of egalitarian triads and helps to maintain the formation of fully and partially connected triadic pattern also in cases of high competitivity. In larger groups of six and seven agents, isolation becomes common, in contrast to groups of four agents where isolation is relatively rare. These results are in concordance with known empirical findings of discourse and participation patterns in small groups.

Suggested Citation

  • Ismo T. Koponen & Maija Nousiainen, 2018. "An Agent-Based Model of Discourse Pattern Formation in Small Groups of Competing and Cooperating Members," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(2), pages 1-1.
  • Handle: RePEc:jas:jasssj:2017-39-3
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    4. Caram, L.F. & Caiafa, C.F. & Proto, A.N. & Ausloos, M., 2010. "Dynamic peer-to-peer competition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(13), pages 2628-2636.
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    Cited by:

    1. Ormazábal, Ignacio & Borotto, Félix A. & Astudillo, Hernán F., 2021. "An agent-based model for teaching–learning processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    2. Philippe Collard, 2022. "The “flat peer learning” agent-based model," Journal of Computational Social Science, Springer, vol. 5(1), pages 161-187, May.

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